Accurately reflecting the evolving data models, mappings, and terminology of the National Cancer Institute's Cancer Research Data Commons (CRDC) in the Metamodel Database (MDB) is crucial for cancer data interoperability.

In this session, Nelson and Mark will demonstrate how to use Liquibase, Neo4j, & Python to manage changes in Neo4j databases like the MDB efficiently. You'll learn how to leverage the Liquichange Python package to generate Liquibase Changelogs with Cypher queries from data model files and implement Liquibase with Neo4j, which provides version control, change previewing, and integration with CI/CD workflows, enabling comprehensive change management capabilities.